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Big Data Hadoop Training Certification Course in Hyderabad

5 1,044 Ratings 1,286 Learners

Intellipaat Big Data Course in Hyderabad lets you master Big Data Hadoop and Spark online to get ready for the Cloudera CCA Spark and Hadoop Developer Certification (CCA175), as well as master Hadoop administration with 14 real-time industry-oriented case-study projects. Get the best Hadoop training in Hyderabad from certified mentors as well as earn IBM Big Data Certificate.

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Key Features

60 Hrs Instructor-led Training
80 Hrs Self-paced Videos
120 Hrs Project Work & Exercises
Flexible Schedule
24 x 7 Lifetime Support & Access
Certification and Job Assistance

Career Transitions

Mahesh Chowdary
Mahesh Chowdary
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Data Scientist intellipaat-image
Nishchay Agrawal
Nishchay Agrawal
Fresher
Data Engineer intellipaat-image
Anil Sharma
Anil Sharma
Customer Support Executive intellipaat-image
AWS Solution Architect intellipaat-image
Herin Wilson
Herin Wilson
Process Associate intellipaat-image
AWS Solution Architect intellipaat-image
Mitali Dhar
Mitali Dhar
Senior Software Engineer intellipaat-image
Project Lead intellipaat-image
Ziyauddin Mulla
Ziyauddin Mulla
Support Executive intellipaat-image
Splunk Administrator intellipaat-image

Course Benefits

5/5 Student Satisfaction Rating
Students Transitioned for Higher Positions
Started a New Career After Completing Our Courses
Got Better Salary Hike and Promotion
Average Salary Per Year $ 9123
Software Developer
Hadoop Administrator
Senior Hadoop Developers
$ 6333 Starting
$ 9123 Median
$ 21807 Experienced
Companies Hiring Big Data Hadoop Professionals
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And 1,000+ Global Companies

Big Data Hadoop Course in Hyderabad Overview

Intellipaat is the pioneer in Big Data Hadoop training in Hyderabad. Intellipaat offers an industry-designed, career-oriented Big Data Hadoop certification training that is in line with clearing the Cloudera certification exam. This is a master’s program that gives you hands-on experience for pursuing a career in Hadoop development, administration, analysis and testing roles. At the end of the training program and upon the successful completion of the IBM project, you will be awarded the IBM certification.

What will you learn in this Big Data course in Hyderabad?

  • Entire Hadoop ecosystem and all its components
  • Working with Hadoop clusters and managing, monitoring and scheduling it
  • Working exclusively with HBase, Hive, Pig, Oozie, Sqoop and Flume
  • Deploying Spark and Storm and writing Scala, Java and Python applications
  • Connecting MapReduce, Hive and Pig with ETL tools
  • Hadoop testing using MRUnit and other automation tools

Analytics, Data Warehouse, Software, Mainframe and BI Professionals, and others

Anybody can take up this training course regardless of their prior skills. Along with this course, you will get the complimentary Linux and Java courses from Intellipaat.

Hyderabad is one of the top IT cities of India, and it rightly goes with the sobriquet of a HITEC city. There are incredible job opportunities in Hyderabad for Hadoop professionals with the right set of skills and professional certifications.

A Cloudera Certified Hadoop Developer in Hyderabad can earn an average salary of ₹1,700,000 per year – Indeed

There will be a shortage of nearly 2 lakh Data Scientists in India by the end of 2018 as per the leading Indian national daily, The Hindu.

Hyderabad enjoys the patronage of some of the biggest IT, e-commerce, electronics, manufacturing, hospitality and financial enterprises from around the world. This combined with the rapidly growing startup culture in the HITEC city of India means that there is an insatiable demand for Hadoop professionals. The demand for qualified and certified Hadoop professionals far outstrips the supply.

Due to this, the Hadoop market trend in Hyderabad is only going one way: upwards.

According to the research by Allied Market Research, global Hadoop market is expected to reach at $84.6 billion by 2021.

Today, our world is generating unprecedented amounts of data, and it needs brute processing and storage capabilities. All these evidences point to the fact that Hadoop is the only framework that can stand up to such a massive onslaught of Big Data deluge. Deploying Hadoop in an organization is no longer optional but critical to the success regardless of the organization’s market size and customer orientation.

Intellipaat provides the most definitive and forward-looking Big Data and Hadoop training course that meets the exacting needs of industries. This training, along with the Cloudera certification, can help you grab top-notch jobs in the Big Data Hadoop world.

At Intellipaat, our stress has always been on getting hands-on experience rather than learning the theoretical and conceptual aspects. This is the reason why as part of this Big Data and Hadoop training you will exclusively work on 14 real-life projects that has over 70 datasets with over a billion data points.

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Information is the oil of the 21st century, and analytics is the combustion engine - Peter Sondergaard, Gartner
The global Hadoop big data analytics market size is expected to grow from USD 12.8 billion in 2020 to USD 23.5 billion by 2025. - MarketsandMarkets

Skills Covered

  • Spark
  • Scala
  • Sqoop
  • Pig
  • Apache Flume
  • Hive
  • HCatalog
  • AVRO
  • Scala REPL
  • SBT/Eclipse
  • Apache Kafka
  • Spark Streaming
  • Impala
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Fees

Self Paced Training

  • 80 Hrs e-learning videos
  • Lifetime Free Upgrade
  • 24 x 7 Lifetime Support & Access
$264

Online Classroom preferred

  • Everything in self-paced, plus
  • 60 Hrs of Instructor-led Training
  • 1:1 Doubt Resolution Sessions
  • Attend as many batches for Lifetime
  • Flexible Schedule
  • 28 Nov
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
  • 01 Dec
  • TUE - FRI
  • 07:00 AM TO 09:00 AM IST (GMT +5:30)
  • 05 Dec
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
  • 12 Dec
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
$ 449 $399 10% OFF Expires in

Corporate Training

  • Customized Learning
  • Enterprise-grade Learning Management System (LMS)
  • 24x7 Support
  • Strong Reporting

Big Data Hadoop Course Content in Hyderabad

Module 01 - Hadoop Installation and Setup Preview

1.1 The architecture of Hadoop cluster
1.2 What is High Availability and Federation?
1.3 How to setup a production cluster?
1.4 Various shell commands in Hadoop
1.5 Understanding configuration files in Hadoop
1.6 Installing a single node cluster with Cloudera Manager
1.7 Understanding Spark, Scala, Sqoop, Pig, and Flume

Module 02 - Introduction to Big Data Hadoop and Understanding HDFS and MapReduce

2.1 Introducing Big Data and Hadoop
2.2 What is Big Data and where does Hadoop fit in?
2.3 Two important Hadoop ecosystem components, namely, MapReduce and HDFS
2.4 In-depth Hadoop Distributed File System – Replications, Block Size, Secondary Name node, High Availability and in-depth YARN – resource manager and node manager

Hands-on Exercise:

1. HDFS working mechanism
2. Data replication process
3. How to determine the size of the block?
4. Understanding a data node and name node

3.1 Learning the working mechanism of MapReduce
3.2 Understanding the mapping and reducing stages in MR
3.3 Various terminologies in MR like Input Format, Output Format, Partitioners, Combiners, Shuffle, and Sort

Hands-on Exercise:

1. How to write a WordCount program in MapReduce?
2. How to write a Custom Partitioner?
3. What is a MapReduce Combiner?
4. How to run a job in a local job runner
5. Deploying a unit test
6. What is a map side join and reduce side join?
7. What is a tool runner?
8. How to use counters, dataset joining with map side, and reduce side joins?

4.1 Introducing Hadoop Hive
4.2 Detailed architecture of Hive
4.3 Comparing Hive with Pig and RDBMS
4.4 Working with Hive Query Language
4.5 Creation of a database, table, group by and other clauses
4.6 Various types of Hive tables, HCatalog
4.7 Storing the Hive Results, Hive partitioning, and Buckets

Hands-on Exercise:

1. Database creation in Hive
2. Dropping a database
3. Hive table creation
4. How to change the database?
5. Data loading
6. Dropping and altering table
7. Pulling data by writing Hive queries with filter conditions
8. Table partitioning in Hive
9. What is a group by clause?

5.1 Indexing in Hive
5.2 The ap Side Join in Hive
5.3 Working with complex data types
5.4 The Hive user-defined functions
5.5 Introduction to Impala
5.6 Comparing Hive with Impala
5.7 The detailed architecture of Impala

Hands-on Exercise: 

1. How to work with Hive queries?
2. The process of joining the table and writing indexes
3. External table and sequence table deployment
4. Data storage in a different table

6.1 Apache Pig introduction and its various features
6.2 Various data types and schema in Hive
6.3 The available functions in Pig, Hive Bags, Tuples, and Fields

Hands-on Exercise: 

1. Working with Pig in MapReduce and local mode
2. Loading of data
3. Limiting data to 4 rows
4. Storing the data into files and working with Group By, Filter By, Distinct, Cross, Split in Hive

7.1 Apache Sqoop introduction
7.2 Importing and exporting data
7.3 Performance improvement with Sqoop
7.4 Sqoop limitations
7.5 Introduction to Flume and understanding the architecture of Flume
7.6 What is HBase and the CAP theorem?

Hands-on Exercise: 

1. Working with Flume to generate Sequence Number and consume it
2. Using the Flume Agent to consume the Twitter data
3. Using AVRO to create Hive Table
4. AVRO with Pig
5. Creating Table in HBase
6. Deploying Disable, Scan, and Enable Table

8.1 Using Scala for writing Apache Spark applications
8.2 Detailed study of Scala
8.3 The need for Scala
8.4 The concept of object-oriented programming
8.5 Executing the Scala code
8.6 Various classes in Scala like getters, setters, constructors, abstract, extending objects, overriding methods
8.7 The Java and Scala interoperability
8.8 The concept of functional programming and anonymous functions
8.9 Bobsrockets package and comparing the mutable and immutable collections
8.10 Scala REPL, Lazy Values, Control Structures in Scala, Directed Acyclic Graph (DAG), first Spark application using SBT/Eclipse, Spark Web UI, Spark in Hadoop ecosystem.

Hands-on Exercise:

1. Writing Spark application using Scala
2. Understanding the robustness of Scala for Spark real-time analytics operation

9.1 Detailed Apache Spark and its various features
9.2 Comparing with Hadoop
9.3 Various Spark components
9.4 Combining HDFS with Spark and Scalding
9.5 Introduction to Scala
9.6 Importance of Scala and RDD

Hands-on Exercise: 

1. The Resilient Distributed Dataset (RDD) in Spark
2. How does it help to speed up Big Data processing?

10.1 Understanding the Spark RDD operations
10.2 Comparison of Spark with MapReduce
10.3 What is a Spark transformation?
10.4 Loading data in Spark
10.5 Types of RDD operations viz. transformation and action
10.6 What is a Key/Value pair?

Hands-on Exercise: 

1. How to deploy RDD with HDFS?
2. Using the in-memory dataset
3. Using file for RDD
4. How to define the base RDD from an external file?
5. Deploying RDD via transformation
6. Using the Map and Reduce functions
7. Working on word count and count log severity

11.1 The detailed Spark SQL
11.2 The significance of SQL in Spark for working with structured data processing
11.3 Spark SQL JSON support
11.4 Working with XML data and parquet files
11.5 Creating Hive Context
11.6 Writing Data Frame to Hive
11.7 How to read a JDBC file?
11.8 Significance of a Spark data frame
11.9 How to create a data frame?
11.10 What is schema manual inferring?
11.11 Work with CSV files, JDBC table reading, data conversion from Data Frame to JDBC, Spark SQL user-defined functions, shared variable, and accumulators
11.12 How to query and transform data in Data Frames?
11.13 How data frame provides the benefits of both Spark RDD and Spark SQL?
11.14 Deploying Hive on Spark as the execution engine

Hands-on Exercise:

1. Data querying and transformation using Data Frames
2. Finding out the benefits of Data Frames over Spark SQL and Spark RDD

12.1 Introduction to Spark MLlib
12.2 Understanding various algorithms
12.3 What is Spark iterative algorithm?
12.4 Spark graph processing analysis
12.5 Introducing Machine Learning
12.6 K-Means clustering
12.7 Spark variables like shared and broadcast variables
12.8 What are accumulators?
12.9 Various ML algorithms supported by MLlib
12.10 Linear regression, logistic regression, decision tree, random forest, and K-means clustering techniques

Hands-on Exercise: 

1. Building a recommendation engine

13.1 Why Kafka?
13.2 What is Kafka?
13.3 Kafka architecture
13.4 Kafka workflow
13.5 Configuring Kafka cluster
13.6 Basic operations
13.7 Kafka monitoring tools
13.8 Integrating Apache Flume and Apache Kafka

Hands-on Exercise:

1. Configuring Single Node Single Broker Cluster
2. Configuring Single Node Multi Broker Cluster
3. Producing and consuming messages
4. Integrating Apache Flume and Apache Kafka.

14.1 Introduction to Spark streaming
14.2 The architecture of Spark streaming
14.3 Working with the Spark streaming program
14.4 Processing data using Spark streaming
14.5 Requesting count and DStream
14.6 Multi-batch and sliding window operations
14.7 Working with advanced data sources
14.8 Features of Spark streaming
14.9 Spark Streaming workflow
14.10 Initializing StreamingContext
14.11 Discretized Streams (DStreams)
14.12 Input DStreams and Receivers
14.13 Transformations on DStreams
14.14 Output Operations on DStreams
14.15 Windowed operators and its uses
14.16 Important Windowed operators and Stateful operators

Hands-on Exercise:

1. Twitter Sentiment analysis
2. Streaming using Netcat server
3. Kafka-Spark streaming
4. Spark-Flume streaming

15.1 Create a 4-node Hadoop cluster setup
15.2 Running the MapReduce Jobs on the Hadoop cluster
15.3 Successfully running the MapReduce code
15.4 Working with the Cloudera Manager setup

Hands-on Exercise:

1. The method to build a multi-node Hadoop cluster using an Amazon EC2 instance
2. Working with the Cloudera Manager

16.1 Overview of Hadoop configuration
16.2 The importance of Hadoop configuration file
16.3 The various parameters and values of configuration
16.4 The HDFS parameters and MapReduce parameters
16.5 Setting up the Hadoop environment
16.6 The Include and Exclude configuration files
16.7 The administration and maintenance of name node, data node directory structures, and files
16.8 What is a File system image?
16.9 Understanding Edit log

Hands-on Exercise:

1. The process of performance tuning in MapReduce

17.1 Introduction to the checkpoint procedure, name node failure
17.2 How to ensure the recovery procedure, Safe Mode, Metadata and Data backup, various potential problems and solutions, what to look for and how to add and remove nodes

Hands-on Exercise:

1. How to go about ensuring the MapReduce File System Recovery for different scenarios
2. JMX monitoring of the Hadoop cluster
3. How to use the logs and stack traces for monitoring and troubleshooting
4. Using the Job Scheduler for scheduling jobs in the same cluster
5. Getting the MapReduce job submission flow
6. FIFO schedule
7. Getting to know the Fair Scheduler and its configuration

18.1 How ETL tools work in Big Data industry?
18.2 Introduction to ETL and data warehousing
18.3 Working with prominent use cases of Big Data in ETL industry
18.4 End-to-end ETL PoC showing Big Data integration with ETL tool

Hands-on Exercise:

1. Connecting to HDFS from ETL tool
2. Moving data from Local system to HDFS
3. Moving data from DBMS to HDFS,
4. Working with Hive with ETL Tool
5. Creating MapReduce job in ETL tool

19.1 Working towards the solution of the Hadoop project solution
19.2 Its problem statements and the possible solution outcomes
19.3 Preparing for the Cloudera certifications
19.4 Points to focus on scoring the highest marks
19.5 Tips for cracking Hadoop interview questions

Hands-on Exercise:

1. The project of a real-world high value Big Data Hadoop application
2. Getting the right solution based on the criteria set by the Intellipaat team

Following topics will be available only in self-paced mode:

20.1 Importance of testing
20.2 Unit testing, Integration testing, Performance testing, Diagnostics, Nightly QA test, Benchmark and end-to-end tests, Functional testing, Release certification testing, Security testing, Scalability testing, Commissioning and Decommissioning of data nodes testing, Reliability testing, and Release testing

21.1 Understanding the Requirement
21.2 Preparation of the Testing Estimation
21.3 Test Cases, Test Data, Test Bed Creation, Test Execution, Defect Reporting, Defect Retest, Daily Status report delivery, Test completion, ETL testing at every stage (HDFS, Hive and HBase) while loading the input (logs, files, records, etc.) using Sqoop/Flume which includes but not limited to data verification, Reconciliation, User Authorization and Authentication testing (Groups, Users, Privileges, etc.), reporting defects to the development team or manager and driving them to closure
21.4 Consolidating all the defects and create defect reports
21.5 Validating new feature and issues in Core Hadoop

22.1 Report defects to the development team or manager and driving them to closure
22.2 Consolidate all the defects and create defect reports
22.3 Responsible for creating a testing framework called MRUnit for testing of MapReduce programs

23.1 Automation testing using the OOZIE
23.2 Data validation using the query surge tool

24.1 Test plan for HDFS upgrade
24.2 Test automation and result

25.1 Test, install and configure

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60
Hours of Instructor-led Training
80
Hours of Self-paced Videos
7
Guided Projects to Practice
24/7
Lifetime Technical Support

Free Career Counselling

Big Data Hadoop Course Projects

Working with MapReduce, Hive, and Sqoop

In this project, you will successfully import data using Sqoop into HDFS for data analysis. The transfer will be from Sqoop data transfer from RDBMS to Hadoop. You will code in Hive query language and carry out data querying and analysis. You will acquire an understanding of Hive and Sqoop after completion of this project.

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Work on MovieLens Data For Finding the Top Movies

Create the top-ten-movies list using the MovieLens data. For this project, you will use the MapReduce program for working on the data file, Apache Pig for analyzing data, and Apache Hive data warehousing and querying. You will be working with distributed datasets.

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Hadoop YARN Project: End-to-End PoC

Bring the daily incremental data into the Hadoop Distributed File System. As part of the project, you will be using Sqoop commands to bring the data into HDFS, working with the end-to-end flow of transaction data, and the data from HDFS. You will work on a live Hadoop YARN cluster. You will work on the YARN central resource manager.

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Table Partitioning in Hive

In this project, you will learn how to improve the query speed using Hive data partitioning. You will get hands-on experience in partitioning of Hive tables manually, deploying single SQL execution in dynamic partitioning, and bucketing of data to break it into manageable chunks.

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Connecting Pentaho with Hadoop Ecosystem

Deploy ETL for data analysis activities. In this project, you will challenge your working knowledge of ETL and Business Intelligence. You will configure Pentaho to work with Hadoop distribution as well as load, transform, and extract data into the Hadoop cluster.

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Multi-node Cluster Setup

Set up a Hadoop real-time cluster on Amazon EC2. The project will involve installing and configuring Hadoop. You will need to run a Hadoop multi-node using a 4-node cluster on Amazon EC2 and deploy a MapReduce job on the Hadoop cluster. Java will need to be installed as a prerequisite for running Hadoop.

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Hadoop Testing Using MRUnit

In this project, you will be required to test MapReduce applications. You will write JUnit tests using MRUnit for MapReduce applications. You will also be doing mock static methods using PowerMock and Mockito and implementing MapReduce Driver for testing the map and reduce pair

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Hadoop Web Log Analytics

Derive insights from web log data. The project involves the aggregation of log data, implementation of Apache Flume for data transportation, and processing of data and generating analytics. You will learn to use workflow and data cleansing using MapReduce, Pig, or Spark.

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Hadoop Maintenance

Through this project, you will learn how to administer a Hadoop cluster for maintaining and managing it. You will be working with the name node directory structure, audit logging, data node block scanner, balancer, Failover, fencing, DISTCP, and Hadoop file formats.

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Twitter Sentiment Analysis

Find out what is the reaction of the people to the demonetization move by India by analyzing their tweets. You will have to download the tweets, load them into Pig storage, divide the tweets into words to calculate sentiment, rate the words from +5 to −5 on the AFFIN dictionary, filter them and analyze sentiment.

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Analyzing IPL T20 Cricket

This project will require you to analyze an entire cricket match and get any details of the match. You will need to load the IPL dataset into HDFS. You will then analyze that data using Apache Pig or Hive. Based on the user queries, the system will have to give the right output.

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Movie Recommendation

Recommend the most appropriate movie to a user based on his taste. This is a hands-on Apache Spark project, which will include the creation of collaborative filtering, regression, clustering, and dimensionality reduction. You will need to make use of the Apache Spark MLlib component and statistical analysis.

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Twitter API Integration for Tweet Analysis

Analyze the user sentiment based on a tweet. In this Twitter analysis project, you will integrate the Twitter API and use Python or PHP for developing the essential server-side codes. You will carry out filtering, parsing, and aggregation depending on the tweet analysis requirement.

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Data Exploration Using Spark SQL – Wikipedia Data Set

In this project, you will be making use of the Spark SQL tool for analyzing Wikipedia data. You will be integrating Spark SQL for batch analysis, Machine Learning, visualizing, and processing of data and ETL processes, along with real-time analysis of data.

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Big Data Hadoop Certification in Hyderabad

This training course is designed to help you clear the Cloudera Spark and Hadoop Developer Certification (CCA175) exams. The entire training course content is in line with these certification programs and helps you clear these certification exams with ease and get the best jobs in the top MNCs.

As part of this Big Data Course in Hyderabad, you will be working on real-time projects and assignments that have immense implications in the real-world industry scenarios, thus helping you fast-track your career effortlessly.

At the end of this Big Data Hadoop training in Hyderabad, there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams and help you score better.

Intellipaat Course Completion Certificate will be awarded upon the completion of the project work (after expert review) and upon scoring at least 60% marks in the quiz. Intellipaat certification is well recognized in top 80+ MNCs like Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, etc.

Big Data Hadoop Training Reviews in Hyderabad

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Joel bassa

Solution Architect

I'm really thankful to Intellipaat about the Hadoop Architect Course with Big Data certification. First of all, the team supported me in finding the best Big Data online course based on my experiences and current assignment. Also, the session is so practical, and the trainers are seasoned and available for any queries even in offline mode after the sessions of Big Data Hadoop course. I'm really recommending this training to anyone who wants to understand the concept of Big Data by learning Hadoop and its ecosystem and obtain a most valuable certification in Hadoop from a recognized institution.

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Nandini Shankar

Senior Software Engineer at ACC Limited

A big thank you to the entire Intellipaat Big Data Hadoop Team! You have delivered a great Hadoop online certification training course, with equally informative Hadoop online tutorials, Big Data video tutorials that are absolutely free. Highly experienced and qualified Big Data Hadoop trainers made the learning process completely effortless and enjoyable for me. I am extremely happy for having enrolled for the best Hadoop training!

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Matt Peter

Hadoop Developer at Tata Consultancy Services

This online big data Hadoop training is extremely industry-focused and job-oriented. Overall I am giving 10 out of 10 for this Hadoop certification course from Intellipaat!

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Mohit Rana

Hadoop Architect at Cognizant

I mastered Hadoop through the Intellipaat Big Data Hadoop online training. Let me frankly tell you that this course is designed in a unique and comprehensive manner that is by far the best. Plus you get loads of free tutorials and video content all along. The entire coursework is easy to understand, very simple language but highly effective from the learner's point of view. There is a natural flow in the big data Hadoop online training course offered by Intellipaat. This is highly recommended for getting the Hadoop certification.

Rich Baker

Director at SBD System

This Intellipaat Hadoop tutorial has delivered more than what they had promised to me. Since I have undergone previous Hadoop training I am quite familiar with Big Data Hadoop concepts but Intellipaat took it to a different level with their attention to details and Hadoop domain expertise. I recommend this training to everybody. You will learn everything from basic Hadoop concepts to advanced Hadoop technology deployment. I am more than satisfied with this training. Thank you Intellipaat!

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Samar Jain

Business Analyst at McKinsey & Company

Thank you very much for your training. The trainer resolved my query in record time and that too as per my utmost sanctification. I have no words to describe my gratitude to Intellipaat.

sheelam Khan

Senior Software Developer at Shopzilla

Recently I completed Big Data Hadoop Certification Training from intellipaat. Great Learning. The best investment I ever made in my career. I've learnt and benefitted a lot from intellipaat big data online course and continue to be a member.

Naman Patni

R&D Software Engineer at Erwin, Inc.

I had taken Intellipaat Big Data Hadoop Online. An excellent online mode of learning. Now I am confident I can look out for a career in Big Data. Upon successfully completing this big data course Thanks again and looking forward to a lot more learning from Intellipaat !! I highly recommend the big data online course. All the best.

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Priyanka Chawla

Big data Developer at Cognizant

I wanted to learn big data online since it had a huge scope. My career changed positively upon completion of Intellipaat Big Data Hadoop Online Training. Go with Intellipaat for a Bright Career !!! Thanks.

Bhuvana

Hadoop, Pig, Hive, HBase, Scala, Spark Trainer

I am completely satisfied with the Intellipaat big data hadoop training. The trainer came with over a decade of industry experience. The entire big data online course was segmented into modules that were created with care so that the learning is complete and as per the industry needs.

Divya

Professional

I am very much happy with the Intellipaat big data Hadoop training. The trainer knowledge and experience was very good. I got more than what I had expected as part of the training program and because of this I could easily master the Hadoop technology. I would recommend the Intellipaat big data course to all.

Bharti Jha

Analyst at Oracle India Pvt. Ltd

Full marks for the Intellipaat support team for providing excellent support services. Hadoop was new to me and I used to have many queries, but the support team was very qualified and very patient in listening to my queries and resolving them to my highest expectations. The entire Big Data course was completely oriented towards the practical aspects.

Amitav Tripathy

Project Manager at Micro Focus

Hi, Intellipaat Big Data course video quality is of the highest level. I had enrolled for the self-paced Big Data Hadoop training online; the videos offered the best platform for learning at one's leisurely pace, since it has been created by industry experts and the attention to detail and real-world examples in the videos are worth mentioning. According to me, this is an industry-recognized Big Data certification training.

Anand

I work as a Senior Technology Architect at Infosys. I work on many projects related to big data technology. After joining Intellipaat one of the best Hadoop training institutes in Hyderabad, I feel more confident in working on hadoop related pojects and the outcome is much better compared to before. Thanks intellipaat team.

Arshiya

Technical Lead | Python Developer

I took hadoop online training course from intellipaat and successfully completed it. I have already started working with big data hadoop team in my company. It feels amazing to be a part of hadoop group I highly recommend this as one of the best Big Data Training institutes in Hyderabad to everybody who wants to make their career in big data domain.

Nischay Agarwal

Big Data Hadoop and Spark Enthusiast

Intellipaat big data Hadoop developer course with spark is a boom for building your skills from beginning to advanced level. As I wanted to start with a big data course but I was not knowing how because I had no idea how to start, from where to start, and what to start, then I finally decided to take a course of big data Hadoop developer from Intellipaat. Intellipaat showed me the right career path to me. After completion of course Intellipaat provided course completion certificate and certificate from IBM . These certificates helped me to stand out among many in interview. Intellipaat - "The Career guide for Big Data Developer"

FAQ’s on Big Data Hadoop Training

Why Should I Learn Big Data Hadoop Training in Hyderabad from Intellipaat?

It is a known fact that the demand for Hadoop professionals far outstrips the supply. So, if you want to learn and make a career in Hadoop, then you need to enroll for Intellipaat Hadoop course online which is the most recognized name in Hadoop training and certification. Intellipaat Hadoop training includes all major components of Big Data and Hadoop like Apache Spark, MapReduce, HBase, HDFS, Pig, Sqoop, Flume, Oozie and more. The entire Intellipaat Big Data training in Hyderabad has been created by industry professionals. You will get 24/7 lifetime support, high-quality course material and videos and free upgrade to latest version of course material. Thus, it is clearly a one-time investment for a lifetime of benefits.

Intellipaat has been serving Big Data Hadoop enthusiasts from every corner of the city. You can be living in any locality in Hyderabad, be it Ameerpet, Gachibowli, HITEC City, Secunderabad, Kukatpally, Dilsukhnagar, Madhapur, Kondapur, Uppal, Banjara Hills, Begumpet, Somajiguda or anywhere. You can have full access to our Hadoop online course sitting at home or office 24/7.

At Intellipaat, you can enroll in either the instructor-led online training or self-paced training. Apart from this, Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience, and they have been actively working as consultants in the same domain, which has made them subject matter experts. Go through the sample videos to check the quality of our trainers.

Intellipaat is offering the 24/7 query resolution, and you can raise a ticket with the dedicated support team at anytime. You can avail of the email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our trainers.

You would be glad to know that you can contact Intellipaat support even after the completion of the training. We also do not put a limit on the number of tickets you can raise for query resolution and doubt clearance.

Intellipaat is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.

You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

Intellipaat actively provides placement assistance to all learners who have successfully completed the training. For this, we are exclusively tied-up with over 80 top MNCs from around the world. This way, you can be placed in outstanding organizations such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation as well.

You can definitely make the switch from self-paced training to online instructor-led training by simply paying the extra amount. You can join the very next batch, which will be duly notified to you.

Once you complete Intellipaat’s training program, working on real-world projects, quizzes, and assignments and scoring at least 60 percent marks in the qualifying exam, you will be awarded Intellipaat’s course completion certificate. This certificate is very well recognized in Intellipaat-affiliated organizations, including over 80 top MNCs from around the world and some of the Fortune 500companies.

Apparently, no. Our job assistance program is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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